Here, we’re just setting a few options.

knitr::opts_chunk$set(
  warning = TRUE, # show warnings during codebook generation
  message = TRUE, # show messages during codebook generation
  error = TRUE, # do not interrupt codebook generation in case of errors,
                # usually better for debugging
  echo = TRUE  # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())

Now, we’re preparing our data for the codebook.

library(codebook)
codebook_data <- rio::import("https://osf.io/s87kd/download", "csv")
# to import an SPSS file from the same folder uncomment and edit the line below
# codebook_data <- rio::import("mydata.sav")
# for Stata
# codebook_data <- rio::import("mydata.dta")
# for CSV
# codebook_data <- rio::import("mydata.csv")

# omit the following lines, if your missing values are already properly labelled
codebook_data <- detect_missing(codebook_data,
    only_labelled = TRUE, # only labelled values are autodetected as
                                   # missing
    negative_values_are_missing = FALSE, # negative values are missing values
    ninety_nine_problems = TRUE,   # 99/999 are missing values, if they
                                   # are more than 5 MAD from the median
    )

# If you are not using formr, the codebook package needs to guess which items
# form a scale. The following line finds item aggregates with names like this:
# scale = scale_1 + scale_2R + scale_3R
# identifying these aggregates allows the codebook function to
# automatically compute reliabilities.
# However, it will not reverse items automatically.
codebook_data <- detect_scales(codebook_data)
## Warning in detect_scales(codebook_data): A items found, but no aggregate
## Warning in detect_scales(codebook_data): C items found, but no aggregate
## Warning in detect_scales(codebook_data): E items found, but no aggregate
## Warning in detect_scales(codebook_data): N items found, but no aggregate
## Warning in detect_scales(codebook_data): O items found, but no aggregate
library(labelled)
## 
## Attaching package: 'labelled'
## The following object is masked from 'package:codebook':
## 
##     to_factor
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
dict <- rio::import("https://osf.io/cs678/download", "csv")

var_label(codebook_data)  <-  dict　 %>% 
  select(variable,  label) %>% 
  dict_to_list()

val_labels(codebook_data$gender) <- c("male"=  1,  "female"=  2)
val_labels(codebook_data$education)  <-  c("in  high  school"=  1,"finished  high  school"=  2,"some  college"=  3,"college  graduate"=  4,"graduate  degree"=  5)

add_likert_labels  <-  function(x){
  val_labels(x)  <-  c("Very  Inaccurate"=  1,
                       "Moderately  Inaccurate"=  2,
                       "Slightly  Inaccurate"=  3,
                       "Slightly  Accurate"=  4,
                       "Moderately  Accurate"=  5,
                       "Very  Accurate"=  6) 
  x
}

likert_items  <-  dict %>% 
  filter(Big6 !="") %>% 
  pull(variable)

codebook_data  <-  codebook_data %>% 
  mutate_at(likert_items,  add_likert_labels)


reversed_items  <-  dict %>% 
  filter  (Keying  ==  -1) %>% 
  pull(variable)

codebook_data  <-  codebook_data　 %>% 
  rename_at(reversed_items,  add_R)

codebook_data  <-  codebook_data　 %>% 
  mutate_at(vars(matches("\\dR$")),reverse_labelled_values)

codebook_data$extraversion  <-  codebook_data　 %>% 
  select(E1R:E5) %>% 
  aggregate_and_document_scale()


metadata(codebook_data)$name  <-  "25 Personality items representing 5 factors"
metadata(codebook_data)$description  <-  "25  personality  self  report  items    taken  from  the  International    Personality  Item  Pool  (ipip.ori.org)"
metadata(codebook_data)$creator  <-  "William  Revelle"
metadata(codebook_data)$citation  <-  "Revelle,  W.,  Wilt,  J.,  &  Rosenthal,  A.    (2010).  Individual  differences  in    cognition:  New  methods  for  examining    the  personality-cognition  link.  In  A.    Gruszka,  G.  Matthews,  &  B.  Szymura    (Eds.),  Handbook  of  individual    differences  in  cognition:  Attention,    memory,  and  executive  control  (pp.    27–49).  New  York,  NY:  Springer."
metadata(codebook_data)$url  <-  "https://CRAN.R-project.org/package=psych"
metadata(codebook_data)$datePublished  <-  "2010-01-01"
metadata(codebook_data)$  temporalCoverage  <-  "Spring 2010"
metadata(codebook_data)$  spatialCoverage  <-  "Online"

Create codebook

codebook(codebook_data)
## Warning in doTryCatch(return(expr), name, parentenv, handler): Reliability CIs
## could not be computed for extraversion
## Warning in doTryCatch(return(expr), name, parentenv, handler): Package "ufs"
## needed to compute reliabilites.
## Warning in value[[3L]](cond): Reliability could not be computed for extraversion
## Warning in value[[3L]](cond): Package "ufs" needed to compute reliabilites.

Metadata

Description

Dataset name: 25 Personality items representing 5 factors

25 personality self report items taken from the International Personality Item Pool (ipip.ori.org)

Metadata for search engines

  • Temporal Coverage: Spring 2010

  • Spatial Coverage: Online

  • Citation: Revelle, W., Wilt, J., & Rosenthal, A. (2010). Individual differences in cognition: New methods for examining the personality-cognition link. In A. Gruszka, G. Matthews, & B. Szymura (Eds.), Handbook of individual differences in cognition: Attention, memory, and executive control (pp. 27–49). New York, NY: Springer.

  • URL: https://CRAN.R-project.org/package=psych

  • Date published: 2010-01-01

  • Creator:

name value
1 William Revelle
x
A1R
A2
A3
A4
A5
C1
C2
C3
C4R
C5R
E1R
E2R
E3
E4
E5
N1R
N2R
N3R
N4R
N5R
O1
O2R
O3
O4
O5R
gender
education
age
extraversion

#Variables

A1R

Am indifferent to the feelings of others.

Distribution

Distribution of values for A1R

Distribution of values for A1R

16 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
A1R Am indifferent to the feelings of others. haven_labelled 16 0.9942857 1 5 6 4.586566 1.407737 6 ▁▂▁▃▃▁▇▇

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

A2

Inquire about others’ well-being.

Distribution

Distribution of values for A2

Distribution of values for A2

27 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
A2 Inquire about others’ well-being. haven_labelled 27 0.9903571 1 5 6 4.80238 1.17202 6 ▁▁▁▁▅▁▇▇

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

A3

Know how to comfort others.

Distribution

Distribution of values for A3

Distribution of values for A3

26 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
A3 Know how to comfort others. haven_labelled 26 0.9907143 1 5 6 4.603821 1.301834 6 ▁▂▁▂▅▁▇▆

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

A4

Love children.

Distribution

Distribution of values for A4

Distribution of values for A4

19 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
A4 Love children. haven_labelled 19 0.9932143 1 5 6 4.699748 1.479633 6 ▁▂▁▁▃▁▅▇

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

A5

Make people feel at ease.

Distribution

Distribution of values for A5

Distribution of values for A5

16 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
A5 Make people feel at ease. haven_labelled 16 0.9942857 1 5 6 4.560345 1.258512 6 ▁▂▁▂▅▁▇▆

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

C1

Am exacting in my work.

Distribution

Distribution of values for C1

Distribution of values for C1

21 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
C1 Am exacting in my work. haven_labelled 21 0.9925 1 5 6 4.502339 1.241346 6 ▁▁▁▂▅▁▇▅

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

C2

Continue until everything is perfect.

Distribution

Distribution of values for C2

Distribution of values for C2

24 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
C2 Continue until everything is perfect. haven_labelled 24 0.9914286 1 5 6 4.369957 1.318347 6 ▁▂▁▂▆▁▇▅

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

C3

Do things according to a plan.

Distribution

Distribution of values for C3

Distribution of values for C3

20 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
C3 Do things according to a plan. haven_labelled 20 0.9928571 1 5 6 4.303957 1.288552 6 ▁▂▁▂▆▁▇▅

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

C4R

Do things in a half-way manner.

Distribution

Distribution of values for C4R

Distribution of values for C4R

26 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
C4R Do things in a half-way manner. haven_labelled 26 0.9907143 1 5 6 4.446647 1.375118 6 ▁▂▁▅▅▁▇▇

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

C5R

Waste my time.

Distribution

Distribution of values for C5R

Distribution of values for C5R

16 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
C5R Waste my time. haven_labelled 16 0.9942857 1 4 6 3.703305 1.628542 6 ▃▆▁▇▅▁▇▆

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

N1R

Get angry easily.

Distribution

Distribution of values for N1R

Distribution of values for N1R

22 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
N1R Get angry easily. haven_labelled 22 0.9921429 1 4 6 4.070914 1.570917 6 ▂▅▁▆▅▁▇▇

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

N2R

Get irritated easily.

Distribution

Distribution of values for N2R

Distribution of values for N2R

21 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
N2R Get irritated easily. haven_labelled 21 0.9925 1 3 6 3.492263 1.525944 6 ▃▆▁▇▅▁▆▃

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

N3R

Have frequent mood swings.

Distribution

Distribution of values for N3R

Distribution of values for N3R

11 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
N3R Have frequent mood swings. haven_labelled 11 0.9960714 1 4 6 3.783435 1.602902 6 ▃▆▁▇▅▁▇▆

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

N4R

Often feel blue.

Distribution

Distribution of values for N4R

Distribution of values for N4R

36 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
N4R Often feel blue. haven_labelled 36 0.9871429 1 4 6 3.814399 1.569685 6 ▃▅▁▇▅▁▇▆

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

N5R

Panic easily.

Distribution

Distribution of values for N5R

Distribution of values for N5R

29 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
N5R Panic easily. haven_labelled 29 0.9896429 1 4 6 4.030314 1.618647 6 ▃▃▁▆▅▁▇▇

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

O1

Am full of ideas.

Distribution

Distribution of values for O1

Distribution of values for O1

22 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
O1 Am full of ideas. haven_labelled 22 0.9921429 1 5 6 4.816055 1.12953 6 ▁▁▁▂▅▁▇▇

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

O2R

Avoid difficult reading material.

Distribution

Distribution of values for O2R

Distribution of values for O2R

0 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
O2R Avoid difficult reading material. haven_labelled 0 1 1 5 6 4.286786 1.565152 6 ▂▃▁▅▃▁▇▇

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

O3

Carry the conversation to a higher level.

Distribution

Distribution of values for O3

Distribution of values for O3

28 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
O3 Carry the conversation to a higher level. haven_labelled 28 0.99 1 5 6 4.438312 1.220901 6 ▁▁▁▂▆▁▇▅

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

O4

Spend time reflecting on things.

Distribution

Distribution of values for O4

Distribution of values for O4

14 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
O4 Spend time reflecting on things. haven_labelled 14 0.995 1 5 6 4.892319 1.22125 6 ▁▁▁▁▃▁▆▇

Value labels

Response choices
name value
Very Inaccurate 1
Moderately Inaccurate 2
Slightly Inaccurate 3
Slightly Accurate 4
Moderately Accurate 5
Very Accurate 6

O5R

Will not probe deeply into a subject.

Distribution

Distribution of values for O5R

Distribution of values for O5R

20 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
O5R Will not probe deeply into a subject. haven_labelled 20 0.9928571 1 5 6 4.510432 1.327959 6 ▁▂▁▃▅▁▇▇

Value labels

Response choices
name value
Very Inaccurate 6
Moderately Inaccurate 5
Slightly Inaccurate 4
Slightly Accurate 3
Moderately Accurate 2
Very Accurate 1

gender

gender

Distribution

Distribution of values for gender

Distribution of values for gender

0 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
gender gender haven_labelled 0 1 1 2 2 1.671786 0.4696471 2 ▃▁▁▁▁▁▁▇

Value labels

Response choices
name value
male 1
female 2

education

education

Distribution

Distribution of values for education

Distribution of values for education

223 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd n_value_labels hist
education education haven_labelled 223 0.9203571 1 3 5 3.190144 1.107714 5 ▂▂▁▇▁▂▁▃

Value labels

Response choices
name value
in high school 1
finished high school 2
some college 3
college graduate 4
graduate degree 5

age

age

Distribution

Distribution of values for age

Distribution of values for age

0 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
age age numeric 0 1 3 26 86 28.78214 11.12755 ▃▇▂▁▁

Scale: extraversion

Overview

Reliability: Not computed.

Missing: 87.

Likert plot of scale extraversion items

Likert plot of scale extraversion items

Distribution of scale extraversion

Distribution of scale extraversion

Reliability details

Summary statistics

name label data_type value_labels n_missing complete_rate min median max mean sd n_value_labels hist
E1R Don’t talk a lot. haven_labelled 6. Very Inaccurate,
5. Moderately Inaccurate,
4. Slightly Inaccurate,
3. Slightly Accurate,
2. Moderately Accurate,
1. Very Accurate		 23 0.9917857 1 4 6 4.025567 1.631506 6 ▃▅▁▆▅▁▇▇
E2R Find it difficult to approach others. haven_labelled 6. Very Inaccurate,
5. Moderately Inaccurate,
4. Slightly Inaccurate,
3. Slightly Accurate,
2. Moderately Accurate,
1. Very Accurate		 16 0.9942857 1 4 6 3.858118 1.605210 6 ▃▅▁▇▅▁▇▆
E3 Know how to captivate people. haven_labelled 1. Very Inaccurate,
2. Moderately Inaccurate,
3. Slightly Inaccurate,
4. Slightly Accurate,
5. Moderately Accurate,
6. Very Accurate		 25 0.9910714 1 4 6 4.000721 1.352719 6 ▂▃▁▃▇▁▇▃
E4 Make friends easily. haven_labelled 1. Very Inaccurate,
2. Moderately Inaccurate,
3. Slightly Inaccurate,
4. Slightly Accurate,
5. Moderately Accurate,
6. Very Accurate		 9 0.9967857 1 5 6 4.422429 1.457517 6 ▁▂▁▂▃▁▇▆
E5 Take charge. haven_labelled 1. Very Inaccurate,
2. Moderately Inaccurate,
3. Slightly Inaccurate,
4. Slightly Accurate,
5. Moderately Accurate,
6. Very Accurate		 21 0.9925000 1 5 6 4.416337 1.334768 6 ▁▂▁▂▅▁▇▅

Missingness report

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "25 Personality items representing 5 factors",
  "description": "25  personality  self  report  items    taken  from  the  International    Personality  Item  Pool  (ipip.ori.org)\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name         |label                                     | n_missing|\n|:------------|:-----------------------------------------|---------:|\n|A1R          |Am indifferent to the feelings of others. |        16|\n|A2           |Inquire about others' well-being.         |        27|\n|A3           |Know how to comfort others.               |        26|\n|A4           |Love children.                            |        19|\n|A5           |Make people feel at ease.                 |        16|\n|C1           |Am exacting in my work.                   |        21|\n|C2           |Continue until everything is perfect.     |        24|\n|C3           |Do things according to a plan.            |        20|\n|C4R          |Do things in a half-way manner.           |        26|\n|C5R          |Waste my time.                            |        16|\n|E1R          |Don't talk a lot.                         |        23|\n|E2R          |Find it difficult to approach others.     |        16|\n|E3           |Know how to captivate people.             |        25|\n|E4           |Make friends easily.                      |         9|\n|E5           |Take charge.                              |        21|\n|N1R          |Get angry easily.                         |        22|\n|N2R          |Get irritated easily.                     |        21|\n|N3R          |Have frequent mood swings.                |        11|\n|N4R          |Often feel blue.                          |        36|\n|N5R          |Panic easily.                             |        29|\n|O1           |Am full of ideas.                         |        22|\n|O2R          |Avoid difficult reading material.         |         0|\n|O3           |Carry the conversation to a higher level. |        28|\n|O4           |Spend time reflecting on things.          |        14|\n|O5R          |Will not probe deeply into a subject.     |        20|\n|gender       |gender                                    |         0|\n|education    |education                                 |       223|\n|age          |age                                       |         0|\n|extraversion |5 E items aggregated by rowMeans          |        87|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
  "creator": "William  Revelle",
  "citation": "Revelle,  W.,  Wilt,  J.,  &  Rosenthal,  A.    (2010).  Individual  differences  in    cognition:  New  methods  for  examining    the  personality-cognition  link.  In  A.    Gruszka,  G.  Matthews,  &  B.  Szymura    (Eds.),  Handbook  of  individual    differences  in  cognition:  Attention,    memory,  and  executive  control  (pp.    27–49).  New  York,  NY:  Springer.",
  "url": "https://CRAN.R-project.org/package=psych",
  "datePublished": "2010-01-01",
  "temporalCoverage": "Spring 2010",
  "spatialCoverage": "Online",
  "keywords": ["A1R", "A2", "A3", "A4", "A5", "C1", "C2", "C3", "C4R", "C5R", "E1R", "E2R", "E3", "E4", "E5", "N1R", "N2R", "N3R", "N4R", "N5R", "O1", "O2R", "O3", "O4", "O5R", "gender", "education", "age", "extraversion"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "A1R",
      "description": "Am indifferent to the feelings of others.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "A2",
      "description": "Inquire about others' well-being.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "A3",
      "description": "Know how to comfort others.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "A4",
      "description": "Love children.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "A5",
      "description": "Make people feel at ease.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "C1",
      "description": "Am exacting in my work.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "C2",
      "description": "Continue until everything is perfect.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "C3",
      "description": "Do things according to a plan.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "C4R",
      "description": "Do things in a half-way manner.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "C5R",
      "description": "Waste my time.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "E1R",
      "description": "Don't talk a lot.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "E2R",
      "description": "Find it difficult to approach others.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "E3",
      "description": "Know how to captivate people.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "E4",
      "description": "Make friends easily.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "E5",
      "description": "Take charge.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "N1R",
      "description": "Get angry easily.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "N2R",
      "description": "Get irritated easily.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "N3R",
      "description": "Have frequent mood swings.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "N4R",
      "description": "Often feel blue.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "N5R",
      "description": "Panic easily.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "O1",
      "description": "Am full of ideas.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "O2R",
      "description": "Avoid difficult reading material.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "O3",
      "description": "Carry the conversation to a higher level.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "O4",
      "description": "Spend time reflecting on things.",
      "value": "1. Very  Inaccurate,\n2. Moderately  Inaccurate,\n3. Slightly  Inaccurate,\n4. Slightly  Accurate,\n5. Moderately  Accurate,\n6. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "O5R",
      "description": "Will not probe deeply into a subject.",
      "value": "6. Very  Inaccurate,\n5. Moderately  Inaccurate,\n4. Slightly  Inaccurate,\n3. Slightly  Accurate,\n2. Moderately  Accurate,\n1. Very  Accurate",
      "maxValue": 6,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "gender",
      "description": "gender",
      "value": "1. male,\n2. female",
      "maxValue": 2,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "education",
      "description": "education",
      "value": "1. in  high  school,\n2. finished  high  school,\n3. some  college,\n4. college  graduate,\n5. graduate  degree",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "age",
      "description": "age",
      "@type": "propertyValue"
    },
    {
      "name": "extraversion",
      "description": "5 E items aggregated by rowMeans",
      "@type": "propertyValue"
    }
  ]
}`